Increasing Freshwater Salinity Impacts Aerosolized Bacteria

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Abstract

Previous results have demonstrated that adherence of Clostridium difficile to tissue culture cells is augmented by various stresses; this study focussed on whether the GroEL heat shock protein is implicated in this process. The 1940 bp groESL operon of C. difficile was isolated by PCR. The 1623 bp groEL gene is highly conserved between various C. difficile isolates as determined by RFLP-PCR and DNA sequencing, and the operon is present in one copy on the bacterial chromosome. The 58 kDa GroEL protein was expressed in Escherichia coli in fusion with glutathione S:-transferase and the fusion protein was purified from IPTG-induced bacterial lysates by affinity chromatography on glutathione-Sepharose. A polyclonal, monospecific antiserum was obtained for GroEL which established by immunoelectron microscopy, indirect immunofluorescence and immunoblot analysis that GroEL is released extracellularly after heat shock and can be surface associated. Cell fractionation experiments suggest that GroEL is predominantly cytoplasmic and membrane bound. GroEL-specific antibodies as well as the purified protein partially inhibited C. difficile cell attachment and expression of the protein was induced by cell contact, suggesting a role for GroEL in cell adherence.

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DADA2: High resolution sample inference from Illumina amplicon data

Benjamin J. Callahan, Paul McMurdie, Michael Rosen … (2016)

We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.

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The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

Christian Quast, Elmar Pruesse, Pelin Yilmaz … (2012)

SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.

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phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

Paul McMurdie, Susan Holmes (2013)

Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.